Recommending Collaboratively Generated Knowledge

Computer Science and Information Systems

Weiqin Chen¹  Richard Persen² 

[1] Department of Information Science and Media Studies;Faculty of Technology, Art and Design

关键词: Recommender systems;    collaborative knowledge;    knowledge building;    emerging learning objects;   

DOI  :  10.2298/CSIS111129017C

学科分类：社会科学、人文和艺术（综合）

来源: Computer Science and Information Systems

【 摘 要 】

With the development and adoption of information technologies in education, learners become active producer of knowledge. There is an increasing amount of content generated by learners in their learning process.These emerging learning objects (ELOs) could potentially be valuable as learning resources as well as for assessment purpose. However, the potentials also give rise to new challenges for indexing, sharing, retrieval and recommendation of such learning objects. In this research we have developed a recommender system for emerging learning objects generated in a collaborative knowledge building process and studied the implications and added values of the recommendations. We conducted two evaluations with learners to assess and improve the system�s design and study the quality and effects of the recommendations. From the evaluations, we received generally positive feedback and the results confirm the added values of the recommendations for the knowledge building process.

【 授权许可】

CC BY-NC-ND